U.S. patent application number 11/186878 was filed with the patent office on 2006-01-26 for enrollment apparatus and enrollment method, and authentication apparatus and authentication method.
This patent application is currently assigned to SANYO ELECTRIC CO., LTD.. Invention is credited to Hirofumi Saitoh, Keisuke Watanabe.
Application Number | 20060018523 11/186878 |
Document ID | / |
Family ID | 35657178 |
Filed Date | 2006-01-26 |
United States Patent
Application |
20060018523 |
Kind Code |
A1 |
Saitoh; Hirofumi ; et
al. |
January 26, 2006 |
Enrollment apparatus and enrollment method, and authentication
apparatus and authentication method
Abstract
An input unit receives the input a fingerprint image of a user.
A classification unit classifies the fingerprint image inputted by
the input unit into any of a plurality of groups defined on the
basis of individual differences of the fingerprint. Based on the
classification result of fingerprint width, namely, the type of a
group determined by the classification unit, a switching control
unit selects either a normal fingerprint width feature extraction
processing unit or a narrow fingerprint width feature extraction
processing unit provided in a feature extraction unit. A feature
extraction unit processes the fingerprint image, using processing
methods defined respectively for the plurality of groups. A
verification data preparation unit prepares fingerprint
verification data. A fingerprint identification unit checks the
fingerprint verification data prepared by an identification data
preparation unit against fingerprint identification data enrolled
in a biological information storage unit.
Inventors: |
Saitoh; Hirofumi;
(Ogaki-city, JP) ; Watanabe; Keisuke;
(Mizuho-city, JP) |
Correspondence
Address: |
MCDERMOTT WILL & EMERY LLP
600 13TH STREET, N.W.
WASHINGTON
DC
20005-3096
US
|
Assignee: |
SANYO ELECTRIC CO., LTD.
|
Family ID: |
35657178 |
Appl. No.: |
11/186878 |
Filed: |
July 22, 2005 |
Current U.S.
Class: |
382/124 |
Current CPC
Class: |
G06K 9/001 20130101 |
Class at
Publication: |
382/124 |
International
Class: |
G06K 9/00 20060101
G06K009/00 |
Foreign Application Data
Date |
Code |
Application Number |
Jul 23, 2004 |
JP |
2004-216433 |
Aug 31, 2004 |
JP |
2004-251477 |
Claims
1. An enrollment apparatus, comprising: an input unit which inputs
biological information to be enrolled; a classification unit which
classifies the biological information inputted by said input unit
into any of a plurality of groups defined on the basis of
individual differences of the biological information; and an
enrollment unit which performs enrollment in a manner that the
biological information inputted is associated with the classified
groups.
2. An enrollment apparatus according to claim 1, wherein the
biological information to be inputted to said input unit is
information on a fingerprint, and wherein said classification unit
defines the plurality of groups according to a degree of density in
the fingerprint.
3. An enrollment apparatus according to claim 2, wherein said
classification unit includes: an extraction unit which extracts the
number of ridge lines and the interval thereof in a predetermined
region from the inputted information on a fingerprint; and an
execution unit which classifies the inputted fingerprint
information into any of the plurality of groups, based on the
number of ridge lines and the interval thereof extracted by said
extraction unit.
4. An enrollment apparatus according to claim 1, further comprising
a processing unit which extracts features from the classified
biological information, based on feature extraction methods defined
respectively for the plurality of groups, wherein said enrollment
unit enrolls, as the inputted biological information,
feature-extracted biological information for each of the plurality
of groups.
5. An enrollment apparatus according to claim 2, further comprising
a processing unit which extracts features from the classified
biological information, using feature extraction methods defined
respectively for the plurality of groups, wherein said enrollment
unit enrolls, as the inputted biological information,
feature-extracted biological information for each of the plurality
of groups.
6. An enrollment apparatus according to claim 3, further comprising
a processing unit which extracts features from the classified
biological information, using feature extraction methods defined
respectively for the plurality of groups, wherein said enrollment
unit enrolls, as the inputted biological information,
feature-extracted biological information for each of the plurality
of groups.
7. An enrollment apparatus, comprising: an input unit which inputs
biological information to be enrolled; and a display unit which
classifies and enrolls the inputted biological information into any
of a plurality of groups defined according to individual
differences of the biological information and which simultaneously
displays a classification and enrollment result.
8. An authentication apparatus, comprising: an input unit which
inputs biological information to be authenticated; a classification
unit which classifies the biological information inputted by said
input unit into any of a plurality of groups defined on the basis
of individual differences of the biological information; a
processing unit which extracts features from the classified
biological information, based on feature extraction methods defined
respectively for the plurality of groups; and an authentication
unit which enrolls beforehand biological information to be referred
to for each of the plurality of groups and which authenticates
feature-extracted biological information based on biological
information to be referred to enrolled in a group corresponding to
the classified biological information among the plurality of
groups.
9. An authentication apparatus according to claim 8, wherein the
biological information to be inputted to said input unit is
information on a fingerprint, and wherein said classification unit
defines the plurality of groups according to a degree of density in
the fingerprint.
10. An authentication apparatus according to claim 8, wherein said
classification unit includes: an extraction unit which extracts the
number of ridge lines and the interval thereof in a predetermined
region from the inputted information of a fingerprint; and an
execution unit which classifies the inputted fingerprint
information into any of the plurality of groups, based on the
number of ridge lines and the interval thereof extracted by the
extraction unit.
11. An authentication apparatus, comprising: an input unit which
inputs biological information to be identified; and a display unit
which authenticates the inputted biological information by
classifying them into any of a plurality of groups defined
according to individual differences of the biological information
and which simultaneously displays a classified and identified
result.
12. An enrollment method characterized in that while biological
information inputted is being classified into any of a plurality of
groups defined according to individual differences of the
biological information, features are extracted from the classified
biological information by applying feature extraction methods
defined respectively for the plurality of groups, and
feature-extracted biological information is enrolled for each of
the plurality of groups.
13. An authentication method characterized in that biological
information to be referred to is enrolled beforehand for each of a
plurality of groups defined on the basis of individual differences
of the biological information and while the biological information
inputted is being classified into any of the plurality of groups,
features are extracted from the classified biological information
by applying feature extraction methods defined respectively for the
plurality of groups, and feature-extracted biological information
is authenticated by referring to biological information to be
referred to corresponding to a group that contains the classified
biological information.
14. An enrollment apparatus, comprising: a biological information
acquiring unit which gathers biological information intrinsic to a
human body, from a predetermined region of body; an index value
calculating unit which calculates an index value where the
biological information is put into indices by a predetermined
criterion; a group specifying unit which detects to which of a
plurality of groups the calculated index value belongs, by
referring to a predetermined classification table in which a range
of the index value is divided into the plurality of groups; a
storage region specifying unit which specifies a storage region
corresponding to the detected group among a plurality of storage
regions respectively associated with the plurality of groups; a
biological information recording unit which records the gathered
biological information in the specified storage region; and a
boundary condition determining unit which determines whether a
boundary condition holds or not based on whether or not the
calculated index value lies within a predetermined value from a
boundary of the detected group, wherein when the boundary condition
holds, said storage region specifying unit specifies two storage
regions corresponding respectively to two groups that lie across
the boundary, and wherein when the boundary condition holds, said
biological information recording unit records the gathered
biological information in the specified two storage regions,
respectively.
15. An enrollment apparatus, comprising: a biological information
acquiring unit which gathers biological information intrinsic to a
human body, from a predetermined region of body; an index value
calculating unit which calculates a first index value and a second
index value where the biological information is put into indices
respectively by two criteria; a first group specifying unit which
detects to which of a plurality of groups of first kind the
calculated first index value belongs, by referring to a first
classification table in which a range of the first index value is
divided into the plurality of groups of first kind; a first storage
region specifying unit which specifies a storage region of first
kind, corresponding to the detected group of first kind, among a
plurality of storage regions of first kind corresponding
respectively to the plurality of groups of first kind; a second
group specifying unit which detects to which of a plurality of
groups of second kind the calculated second index value belongs, by
referring to a second classification table in which a range of the
second index value is divided into the plurality of groups of
second kind; a second storage region specifying unit which
specifies a storage region of second kind, corresponding to the
detected group of second kind, among a plurality of storage regions
of second kind corresponding respectively to the plurality of
groups of second kind; and a biological information recording unit
which records the gathered biological information in the specified
storage regions of first kind and second kind, respectively.
16. An authentication apparatus, comprising: a biological
information acquiring unit which gathers biological information
intrinsic to an authenticatee, from a predetermined region of body;
an index value calculating unit which calculates a index value
where the biological information is put into indices by a
predetermined criterion; a group specifying unit which detects to
which of a plurality of groups the calculated index value belongs,
by referring to a predetermined classification table in which a
range of the index value is divided into the plurality of groups; a
storage region specifying unit which specifies a storage region
corresponding to the detected group among a plurality of storage
regions respectively associated with the plurality of groups; a
biological information storage unit which stores biological
information on a same registrant in two or more storage regions
separately; and an authentication unit which authenticates the
authenticatee by checking the biological information gathered from
the authenticatee against biological information, on a registrant,
stored in the specified storage region, wherein when authentication
of the authenticatee fails, said authentication unit checks the
biological information on the authenticatee against biological
information, on the registrant, stored in a storage region that
differs from the specified storage region.
17. An authentication apparatus according to claim 16, further
comprising a boundary condition determining unit which determines
whether a boundary condition holds or not based on whether or not
the calculated index value lies within a predetermined value from a
boundary of the detected group, wherein when the boundary condition
holds, said storage region specifying unit specifies two storage
regions corresponding respectively to two groups that lie across
the boundary, and wherein when the boundary condition holds, said
authentication unit checks the biological information on the
authenticatee against the biological information, on the
registrant, stored in the specified two storage regions.
18. An authentication apparatus, comprising: a biological
information acquiring unit which gathers biological information
intrinsic to a human body, from a predetermined region of body; an
index value calculating unit which calculates a first index value
and a second index value where the biological information is put
into indices respectively by two criteria; a first group specifying
unit which detects to which of a plurality of groups of first kind
the calculated first index value belongs, by referring to a first
classification table in which a range of the first index value is
divided into the plurality of groups of first kind; a first storage
region specifying unit which specifies a storage region of first
kind, corresponding to the detected group of first kind, among a
plurality of storage regions of first kind corresponding
respectively to the plurality of groups of first kind; a second
group specifying unit which detects to which of a plurality of
groups of second kind the calculated second index value belongs, by
referring to a second classification table in which a range of the
second index value is divided into the plurality of groups of
second kind; a second storage region specifying unit which
specifies a storage region of second kind, corresponding to the
detected group of second kind, among a plurality of storage regions
of second kind corresponding respectively to the plurality of
groups of second kind; a biological information storage unit which
stores biological information on a same registrant in the storage
region of first kind and the storage region of second kind
separately; and an authentication unit which authenticates an
authenticatee by checking the biological information gathered from
the authenticatee against biological information, on a registrant,
stored in the specified storage regions of first kind and second
kind.
Description
BACKGROUND OF THE INVENTION
[0001] 1. Field of the Invention
[0002] The present invention relates to the registration technique
and the authentication technology, and it particularly relates to
enrollment method and enrollment apparatus as well as
authentication method and authentication apparatus by which to
carry out a user authentication using biological information.
[0003] 2. Description of the Related Art
[0004] Biometric authentication uses such biological information as
fingerprint, palm print, face image, iris image or voiceprint as
the object to be authenticated. In such biometric authentication,
parameters or the like for feature extraction are fixed for use at
registration and identification of authentication data by tuning
them to typical biological information. In fingerprint-based
authentication, for instance, threshold values, constants and the
like are determined by optimizing the image resolution for image
processing and the various parameters for fingerprint feature
extraction based on a typical fingerprint, such as a fingerprint of
an adult person. In fingerprint identification, therefore, a
certain level of identification accuracy is ensured by image
processing and feature extraction using the thus optimized set
values at enrollment and identification of the user's
fingerprint.
[0005] Suppose that the feature extraction is done with the same
authentication threshold values but using different set values and
conditions between registration and identification, then the
identification reject rate (false nonmatch rate), which is the
probability of not identifying an individual as the same person,
will rise. The identification reject rate may be lowered by loosely
setting the authentication threshold values. But such loose setting
may raise the false identification rate (false match rate), which
is the probability of falsely authenticating individuals other than
the intended one. In practice, therefore, processing parameters are
not changed according to the individual differences of persons to
be identified.
[0006] Also, in biometric authentication, it takes much time to
search the authentication database or perform a verification
processing, and for that reason the users are often classified by
age or gender to speed up the authentication process (See Japanese
Patent Application Laid-Open No. 2002-8035, for instance).
[0007] A user authentication system is normally such that the
resolution of image processing and the filters for feature
extraction are tuned to the typical users. In consequence, there
are cases where the system cannot authenticate persons who have
fingerprints deviant from the typical ones, such as a fingerprint
with finer wrinkles on a smaller finger or a fingerprint on a rough
skin. For such users for whom fingerprint identification cannot be
used, the user authentication system offers some substitute means
like password identification. Such an irregular response, however,
goes counter to the original purpose of biometric authentication,
which is to raise the level of security. Not only fingerprint
authentication but also iris-based authentication or face
identification encounters the problem of individual differences
that require adjustment of the processing parameters for the
individuals to be authenticated. That is, there are, in fact, users
who are not compatible with a user authentication system based on
typical biological information, and this creates inconvenience in
the operation of such a user authentication system. Also, to
improve convenience for the users, it is desirable that the
authentication process be automated.
SUMMARY OF THE INVENTION
[0008] The present invention has been made in view of the foregoing
circumstances and problems, and an object thereof is to provide an
identification technology that can also be used with users not
compatible with ordinary personal authentication systems because of
their nontypical physical characteristics.
[0009] In order to solve the above problems, an enrollment
apparatus according to a preferred mode of carrying out the present
invention comprises: an input unit which inputs biological
information to be enrolled; a classification unit which classifies
the biological information inputted by the input unit into any of a
plurality of groups defined on the basis of individual differences
of the biological information; and an enrollment unit which
performs enrollment in a manner that the biological information
inputted is associated with the classified groups.
[0010] According to this mode of carrying out the present
invention, the biological information inputted is automatically
classified into any of a plurality of groups so that it belongs to
the applicable one of the plurality of groups. As a result, the
convenience for persons involved in authentication processing can
be improved.
[0011] The biological information to be inputted to the input unit
may be information on a fingerprint, and the classification unit
may define the plurality of groups according to a degree of density
in the fingerprint. A group into which the information is to be
classified can be selected based on the degree of density of the
fingerprint.
[0012] The classification unit may includes: an extraction unit
which extracts the number of ridge lines and the interval thereof
in a predetermined region from the inputted information on a
fingerprint; and an execution unit which classifies the inputted
fingerprint information into any of the plurality of groups, based
on the number of ridge lines and the interval thereof extracted by
the extraction unit. The density of a fingerprint can be determined
based on the number of ridge lines and the interval thereof, so
that the fingerprint can be determined with high accuracy. The
classification unit may further include a presentation unit which
presents to a registrant a classification result carried out by the
classification unit. With this presentation unit, the
classification result can be presented to the registrant in the
ensured manner.
[0013] The enrollment apparatus may further comprise a processing
unit which extracts features from the classified biological
information, based on feature extraction methods defined
respectively for the plurality of groups, wherein the enrollment
unit may enroll, as the inputted biological information,
feature-extracted biological information for each of the plurality
of groups. While the biological information inputted is being
automatically classified in such a manner as to belong to the
applicable one of the plurality of groups, the features are
extracted using the feature extraction methods suitable
respectively for the plurality of groups. Hence, the convenience
for the registrants is improved and at the same time the features
can be extracted with high accuracy from the biological
information.
[0014] Another preferred mode of carrying out the present invention
relates also to an enrollment apparatus. This apparatus comprises:
an input unit which inputs biological information to be enrolled;
and a display unit which classifies and enrolls the inputted
biological information into any of a plurality of groups defined
according to individual differences of the biological information
and which simultaneously displays a classification and enrollment
result.
[0015] According to this mode of carrying out the present
invention, the biological information is enrolled for each of
groups classified according to the biological information, so that
a predetermined processing can be performed for each of the
groups.
[0016] Still another preferred mode of carrying out the present
invention relates to an authentication apparatus. This apparatus
comprises: an input unit which inputs biological information to be
authenticated; a classification unit which classifies the
biological information inputted by the input unit into any of a
plurality of groups defined on the basis of individual differences
of the biological information; a processing unit which extracts
features from the classified biological information, based on
feature extraction methods defined respectively for the plurality
of groups; and an authentication unit which enrolls beforehand
biological information to be referred to for each of the plurality
of groups and which authenticates feature-extracted biological
information based on biological information to be referred to
enrolled in a group corresponding to the classified biological
information among the plurality of groups.
[0017] According to this mode of carrying out the present
invention, the biological information to be referred to is
classified into a plurality of groups and enrolled accordingly and
at the same time a group to which the biological information to be
authenticated shall belong is automatically determined and the
authentication is carried out based on the biological information
to be referred to that belongs to the applicable group. Thus, the
convenience for persons involved in authentication processing is
improved, and at the same time the authentication speed and
authentication accuracy can be improved.
[0018] Still another preferred mode of carrying out the present
invention relates also to an authentication apparatus. This
apparatus comprises: an input unit which inputs biological
information to be authenticated; and a display unit which
authenticates the inputted biological information by classifying
them into any of a plurality of groups defined according to
individual differences of the biological information and which
simultaneously displays a classified and identified result.
[0019] According to this mode of carrying out the present
invention, the biological information is authenticated for each of
groups classified according to the biological information, so that
the authentication accuracy is raised and at the same time the
authentication processing can be done at high speed.
[0020] Still another preferred mode of carrying out the present
invention relates to an enrollment method. This method is
characterized in that while biological information inputted is
being classified into any of a plurality of groups defined
according to individual differences of the biological information,
features are extracted from the classified biological information
by applying feature extraction methods defined respectively for the
plurality of groups, and feature-extracted biological information
is enrolled for each of the plurality of groups.
[0021] Still another preferred mode of carrying out the present
invention relates to an authentication method. This method is
characterized in that biological information to be referred to is
enrolled beforehand for each of a plurality of groups defined on
the basis of individual differences of the biological information
and while the biological information inputted is being classified
into any of the plurality of groups, features are extracted from
the classified biological information by applying feature
extraction methods defined respectively for the plurality of
groups, and feature-extracted biological information is
authenticated by referring to biological information to be referred
to corresponding to a group that contains the classified biological
information.
[0022] Still another preferred mode of carrying out the present
invention relates to an enrollment apparatus. In this apparatus,
the biological information acquired is put into indices and to
which of a plurality of groups this index value shall belong is
detected wherein the plurality of groups are such that an index
value is classified beforehand into a plurality of ranges. This
apparatus has a plurality of storage regions respectively
associated with the plurality of groups, and records the biological
information in a storage region corresponding to the detected
group. In so doing, when the index value is close to a boundary of
the group, the biological information gathered is separately
recoded in two storage regions corresponding respectively to two
groups that lie across the boundary.
[0023] According to this mode of carrying out the present
invention, the biological information is recorded in one or more
storage regions corresponding to one or more groups. Even if the
group is set in a narrow sense, the biological information which is
easily classifiable is recorded in a single storage region whereas
the biological information which is hard to be classified is
recorded in a plurality of storage regions. If the biological
information on a person to be identified is hard-to-be-classified
one, the group to be checked is liable to change from one group to
another at the time of identification. Even in such a case, the
biological information on such a registrant is recorded in a
plurality of storage regions, so that the authentication is less
likely to fail. As a result, this structure is effective in keeping
the authentication accuracy high while the advantage in which the
biological information is classified and then enrolled is made full
use of.
[0024] Still another preferred mode of carrying out the present
invention relates also to an enrollment apparatus. In this
apparatus, the biological information acquired is put into indices
by two kinds of index values consisting of a first index value and
a second index value, and to which of a plurality of groups these
index values shall belong is detected wherein the plurality of
groups are such that an index value is classified beforehand into a
plurality of ranges. In this apparatus, the biological information
is separately recoded in a storage region associated to a group
containing the first index and a storage region associated to a
group containing the second index value, respectively.
[0025] According to this mode of carrying out the present
invention, two or more kinds of index values from different
perspectives are calculated for a single piece of biological
information without going through the trouble of acquiring a
plurality of kinds of biological information. And the biological
information is recorded in a plurality of storage regions
corresponding to the plurality of index values. For instance, even
if the biological information on a person to be verified is rather
hard to be classified using the first index value, there are cases
where the classification may be easily done by using the second
index value. As a result, the authentication is less likely to
fail. Thus, this scheme is effective in keeping the authentication
accuracy high while the advantage in which the biological
information is classified and then enrolled is made full use
of.
[0026] Furthermore, according to the personal authentication
performed based on the biological information enrolled in these
enrollment apparatus described above, an authentication apparatus
can be provided such that the biological authentication can be
carried out with high authentication accuracy while the improvement
in authentication speed achieved by ingeniously classifying the
biological information is being enjoyed.
[0027] It is to be noted that any arbitrary combination of the
above-described structural components as well as the expressions
according to the present invention changed among a method, an
apparatus, a system, a recording medium, a computer program and so
forth are all effective as and encompassed by the present
embodiments.
BRIEF DESCRIPTION OF THE DRAWINGS
[0028] FIG. 1 illustrates a structure of a fingerprint enrollment
apparatus according to a first embodiment of the present
invention.
[0029] FIGS. 2A and 2B illustrate groups classified by the
fingerprint enrollment apparatus shown in FIG. 1.
[0030] FIGS. 3A and 3B show examples of display messages to be
given by an enrollment result display unit shown in FIG. 3.
[0031] FIG. 4 illustrates a structure of a classification unit
shown in FIG. 1.
[0032] FIG. 5 illustrates a structure of a fingerprint
authentication apparatus according to the first embodiment of the
present invention.
[0033] FIGS. 6A and 6B show display messages to be given by an
identification result display unit shown in FIG. 5.
[0034] FIG. 7 illustrates a structure of a personal authentication
apparatus according to the first embodiment of the present
invention.
[0035] FIG. 8 is a flowchart showing a fingerprint enrollment
procedure by the fingerprint enrollment apparatus shown in FIG.
1.
[0036] FIG. 9 is a flowchart showing a fingerprint authentication
procedure by the fingerprint authentication apparatus shown in FIG.
5.
[0037] FIG. 10 is a functional block diagram for a personal
authentication apparatus according to a second embodiment of the
present invention.
[0038] FIG. 11 illustrates a data structure in a biological
information storage unit.
[0039] FIG. 12 is a flowchart showing a processing procedure when a
fingerprint is enrolled in a personal authentication apparatus.
[0040] FIG. 13 is a flowchart showing the first example of a
processing procedure in the authentication of fingerprints
according to the second embodiment of the present invention.
[0041] FIG. 14 is a flowchart showing the second example of a
processing procedure in the authentication of fingerprints
according to the second embodiment of the present invention.
DETAILED DESCRIPTION OF THE INVENTION
[0042] The invention will now be described based on the following
embodiments which do not intend to limit the scope of the present
invention but exemplify the invention. All of the features and the
combinations thereof described in the embodiments are not
necessarily essential to the invention.
FIRST EMBODIMENT
[0043] Before describing the present invention in detail, an
outline of the present invention will be described first. A first
embodiment of the present invention relates to a fingerprint
enrollment apparatus that enrolls the fingerprints of users in
advance and a fingerprint authentication apparatus that
authenticates their fingerprints. The fingerprint enrollment
apparatus according to the first embodiment accepts the fingerprint
images of the users and divides them into a group of fingerprints
of normal width (hereinafter referred to as "normal fingerprint
width group") and a group of fingerprints of narrower width
(hereinafter referred to as "narrow fingerprint width group").
There are a previously defined image processing method for the
normal fingerprint width group and that for the narrow fingerprint
width group, and the fingerprint enrollment apparatus extracts
features of a fingerprint image through an image processing using
the image processing method corresponding to the group into which
the received fingerprint image is classified. The fingerprint image
whose features have been extracted is classified and enrolled into
a relevant group as authentication data.
[0044] A fingerprint authentication apparatus according to the
first embodiment receives the fingerprint images of the users. Then
it classifies them in the same way as with the fingerprint
enrollment apparatus, and extracts features of each fingerprint
image through an image processing of the fingerprint image using
the image processing method corresponding to the group into which
the received fingerprint image is classified. The fingerprint image
whose features have been extracted is now to be used as
verification data, and this verification data is authenticated
through comparison with the identification data enrolled in
advance. It is to be noted here that since identification data are
classified and enrolled into their respective groups by the
fingerprint enrollment apparatus, the identification data to be
used is one corresponding to a group to which the verification data
shall properly belong.
[0045] FIG. 1 illustrates a structure of a fingerprint enrollment
apparatus 100 according to the first embodiment of the present
invention. The fingerprint enrollment apparatus 100 includes an
input unit 10, a classification unit 40, a switching control unit
12, a switch 14a, a switch 14b, a feature extraction unit 42, an
identification data preparation unit 18, an identification data
enrollment unit 20 and an enrollment result display unit 22. The
feature extraction unit 42 includes a normal fingerprint width
feature extraction processing unit 16a and a narrow fingerprint
width feature extraction processing unit 16b. A biological
information storage unit 30 contains fingerprint identification
data 32.
[0046] The input unit 10 accepts information on the fingerprint of
a user as the biological information on a person to be enrolled.
The information on a fingerprint is, for instance, a fingerprint
image digitized by a scanner or the like. The classification unit
40 classifies the inputted fingerprint image into the applicable
one of a plurality of groups of fingerprint images which have been
defined according to individual differences. In other words, the
classification unit 40 decides whether the fingerprint width of a
fingerprint image received by the input unit 10 is normal or
narrow. The plurality of groups of fingerprint images are defined
according to the roughness/fineness of fingerprints or the
wideness/narrowness of fingerprints just as the aforementioned
"normal fingerprint width group" and "narrow fingerprint width
group".
[0047] FIGS. 2A and 2B illustrate the groups of fingerprint data,
which are classified by a fingerprint enrollment apparatus 100.
FIG. 2A is an illustration of fingerprint input data 300a belonging
to a user who has a fingerprint of normal width. The fingerprint
input data 300a of a normal fingerprint width has a fingerprint
image 310a of normal fingerprint width and thus belongs to a normal
fingerprint width group 320a. Here, the normal fingerprint width
group 320a is denoted by a symbol "A". On the other hand, FIG. 2B
is an illustration of fingerprint input data 300b belonging to a
user who has a fingerprint of a narrower than normal width. The
fingerprint input: data 300b of a narrow fingerprint width has a
fingerprint image 310b of narrow fingerprint width and thus belongs
to a narrow fingerprint width group 320b. The narrow fingerprint
width group 320b is denoted by a symbol "B". Here, as mentioned
above, the classification unit 40 classifies the fingerprint image
into the normal fingerprint width group 320a or the narrow
fingerprint width group 320b. Although the method of classification
will be described in detail later, the classification unit 40
extracts the number of ridge lines and the interval thereof in a
predetermined region from the inputted fingerprint image.
Furthermore, based on the extracted number and interval of ridge
lines, the classification unit 40 decides whether the fingerprint
image belongs to the normal fingerprint width group 320a or the
narrow fingerprint width group 320b.
[0048] Referring back to FIG. 1, the switching control unit 12
controls switches 14a and 14b based on the result of fingerprint
width classification, namely, the group of fingerprints, determined
by the classification unit 40 and selects the normal fingerprint
width feature extraction processing unit 16a or the narrow
fingerprint width feature extraction processing unit 16b, provided
in the feature extraction unit 42, as applicable. When a
fingerprint belongs to the normal fingerprint width group 320a,
input/output of the feature extraction unit 42 is switched to the
normal fingerprint width feature extraction processing unit 16a
side, whereas when it belongs to the narrow fingerprint width group
320b, input/output of the feature extraction unit 42 is switched to
the narrow fingerprint width feature extraction processing unit 16b
side.
[0049] The feature extraction unit 42 extracts features from a
fingerprint image, using the applicable one of the feature
extraction methods defined respectively for the plurality of
fingerprint width groups. That is, for a fingerprint image 310a of
normal fingerprint width, fingerprint feature data such as feature
points are extracted by the normal fingerprint width feature
extraction processing unit 16a, and for a fingerprint image 310b of
narrow fingerprint width, they are extracted by the narrow
fingerprint width feature extraction processing unit 16b, before
the fingerprint feature data thus extracted are outputted by the
feature extraction unit 42. For example, different window sizes to
be used at the extraction of fingerprint feature data from a
fingerprint image are specified for the normal fingerprint width
feature extraction processor 16a and the narrow fingerprint width
feature extraction processor 16b so that the window size for the
former is larger than that for the latter. Different algorithms for
the extraction of fingerprint feature data from a fingerprint image
may be used for the normal fingerprint width feature extraction
processing unit 16a and the narrow fingerprint width feature
extraction processing unit 16b. In this manner, it is preferable
that at least partially different feature extraction methods be
used for the normal fingerprint width feature extraction processing
unit 16a and the narrow fingerprint width feature extraction
processing unit 16b.
[0050] The identification data preparation unit 18 prepares
fingerprint identification data 32 which hold both the fingerprint
feature data extracted by the feature extraction unit 42 and the
fingerprint width group selected by the switching control unit 12
in a predetermined format. The identification data enrollment unit
20 enrolls fingerprint identification data 32 in the biological
information storage unit 30 respectively under a plurality of
fingerprint groups. That is, fingerprint identification data 32
belonging to the normal fingerprint width group 320a are enrolled
in the region corresponding to the normal fingerprint width group
320a in the biological information storage unit 30, and those
belonging to the narrow fingerprint width group 320b are enrolled
in the region corresponding to the narrow fingerprint width group
320b in the biological information storage unit 30. It is to be
noted that these regions may be separated from one another either
physically or logically.
[0051] The enrollment result display unit 22 indicates to the user
the completion of fingerprint enrollment on a display or the like.
The enrollment result display unit 22 also displays a message
requesting the user to enter a fingerprint image again when the
features could not be extracted adequately and therefore an
enrollment has not been accomplished due to an ill-defined
fingerprint image. Furthermore, the enrollment result display unit
22 may indicate the result of classification by the classification
unit 40, that is, whether the fingerprint belongs to the normal
fingerprint width group 320a or the narrow fingerprint width group
320b. FIGS. 3A and 3B show examples of display messages to be given
by the enrollment result display unit 22. FIG. 3A represents the
case where an inputted fingerprint image belongs to the normal
fingerprint width group 320a, and FIG. 3B represents the case where
it belongs to the narrow fingerprint width group 320b. It is to be
noted here that the enrollment result display unit 22 may not only
give such messages on a display or the like but also convey them to
a PC (personal computer) or the like via a network (not shown).
[0052] In terms of hardware, such a structure as above can be
realized by a CPU, a memory and other LSIs of an arbitrary
computer. In terms of software, it can be realized by memory-loaded
programs or the like, but drawn and described herein are function
blocks that are realized in cooperation with those. Thus, it is
understood by those skilled in the art that these function blocks
can be realized in a variety of forms such as by hardware only,
software only or the combination thereof.
[0053] FIG. 4 illustrates a structure of a classification unit 40.
The classification unit 40 includes a block specifying unit 50, a
ridge direction extracting unit 52, a ridge count and interval
calculating unit 54 and an executing unit 56. The block specifying
unit 50 extracts a block in an inputted fingerprint image where the
fingerprint image exists. For instance, the central area of the
fingerprint image is extracted. To extract the central area of the
fingerprint image, the block specifying unit 50 divides the
fingerprint image into small-sized regions and calculates the
averages of the pixel values of fingerprint image contained in the
respective regions. The block specifying unit 50 then chooses a
region with a large pixel value as the center of the fingerprint
image by comparing the averaged pixel values with one another. And
the block specifying unit 50 specifies as the block an area with a
predetermined width centering around the central region of the
fingerprint image.
[0054] The ridge direction extracting unit 52 derives the ridge
direction of a fingerprint. The ridge direction may be the
tangential direction of ridges, for instance. The ridge count and
interval calculating unit 54 calculates the number of ridges and
the interval thereof in the direction vertical to the derived ridge
direction within the specified block. The executing unit 56
classifies the inputted fingerprint image into an applicable group
based on the ridge direction, ridge count and ridge interval. In
other words, the ridge count and the ridge interval are corrected
according to the ridge direction. For instance, the ridge count and
the ridge interval when the ridges are rotated in such a manner as
to be in a predetermined direction are derived. Then the ridge
count and interval thus corrected are compared with a predetermined
threshold value to decide whether the inputted fingerprint image
belongs to the normal fingerprint width group 320a or the narrow
fingerprint width group 320b.
[0055] FIG. 5 illustrates a structure of a fingerprint
authentication apparatus 200 according to the first embodiment of
the present invention. The fingerprint authentication apparatus 200
includes an input unit 10, a classification unit 40, a switching
control unit 12, a switch 14a, a switch 14b, a feature extraction
unit 42, a verification data preparation unit 28, a fingerprint
identification unit 24 and an identification result display unit
26. The feature extraction unit 42 includes a normal fingerprint
width feature extraction processing unit 16a and a narrow
fingerprint width feature extraction processing unit 16b. A
biological information storage unit 30 contains fingerprint
identification data 32.
[0056] These function blocks may be realized in various forms by
hardware only, by software only or by a combination thereof. The
fingerprint authentication apparatus 200 makes a fingerprint
identification of the user in response to the input of a
fingerprint image by him/her. Of the structure of the fingerprint
authentication apparatus 200, the input unit 10, the classification
unit 40, the switching control unit 12, the switch 14a, the switch
14b and the feature extraction unit 42 are the same as those with
the same reference numerals of the fingerprint enrollment apparatus
100 shown in FIG. 1, and therefore their repeated explanation is
omitted herein.
[0057] The verification data preparation unit 28 prepares
fingerprint verification data which hold both the fingerprint
feature data extracted by the feature extraction unit 42 and the
fingerprint width group selected by the switching control unit 12
in a predetermined format. The fingerprint identification unit 24
compares the fingerprint verification data prepared by the
verification data preparation unit 28 with the fingerprint
identification data 32 enrolled in the biological information
storage unit 30 to see if there is any match. In particular, the
fingerprint identification unit 24 verifies the fingerprint
verification data based on the fingerprint identification data 32
enrolled in the fingerprint width group selected by the switching
control unit 12 from the plurality of fingerprint width groups. For
example, if the fingerprint verification data belong to the normal
fingerprint width group 320a, then the fingerprint identification
unit 24 will carry out an authentication using the fingerprint
identification data 32 enrolled in the normal fingerprint width
group 320a of the biological information storage unit 30. The
authentication may be carried out by examining the correspondence
between the line segments connecting feature points contained in
each of the fingerprint identification data 32 and the fingerprint
verification data.
[0058] When a fingerprint is judged to belong to an enrolled user
as a result of verification by the fingerprint identification unit
24, the identification result display unit 26 displays a message
for the user indicating the success of authentication. On the other
hand, when a fingerprint has no match among the fingerprints of all
the enrolled users, the identification result display unit 26
displays a message for the user indicating the failure of
authentication. FIGS. 6A and 6B show examples of display messages
to be given by the identification result display unit 26. FIG. 6A
represents the case where authentication has been successful, and
FIG. 6B the case where authentication has been unsuccessful. It is
to be noted here that the authentication result display unit 26 may
not only give such messages on a display or the like but also
convey them to a PC (personal computer) or the like via a network
(not shown).
[0059] FIG. 7 illustrates a, structure of a personal authentication
apparatus according to the first embodiment of the present
invention. This identity authentication system is so structured
that a fingerprint enrollment apparatus 100 as shown in FIG. 1 and
a fingerprint authentication apparatus 200 as shown in FIG. 2
access and share a biological information storage unit 30. The
biological information storage unit 30 is so structured that a
normal fingerprint width identification database 34 and a narrow
fingerprint width identification database 36 are stored in
physically or logically separate regions. Here, the normal
fingerprint width identification database 34 is a database
corresponding to the aforementioned normal fingerprint width group
320a, whereas the narrow fingerprint width identification database
36 is a database corresponding to the aforementioned narrow
fingerprint width group 320b.
[0060] At the time of registration, a user inputs a fingerprint
image to the fingerprint enrollment apparatus 100, and thereupon
the fingerprint enrollment apparatus 100 classifies the inputted
fingerprint image as fingerprint input data 300a of normal
fingerprint width, prepares fingerprint identification data 32
using the feature extraction processing for normal fingerprint
width, and enrolls the thus prepared data in the normal fingerprint
width identification database 34.
[0061] At the time of authentication, another user inputs a
fingerprint image to the fingerprint authentication apparatus 200,
and thereupon the fingerprint authentication apparatus 200
classifies the inputted fingerprint image as fingerprint input data
300b of narrow fingerprint width, prepares fingerprint verification
data using the feature extraction processing for narrow fingerprint
width, compares it with the fingerprint identification data 32 for
enrolled users of the narrow fingerprint width identification
database 36 and displays a message indicating the success or
failure of authentication.
[0062] Since the biological information storage unit 30 is divided
into two databases, namely, the normal fingerprint width
identification database 34 and the narrow fingerprint width
identification database 36, according to the fingerprint width,
this system presents such advantages as high-speed search due to
the halved amount of verification and improved identification
accuracy on account of the limited amount of verification.
[0063] A fingerprint enrollment procedure and a fingerprint
authentication procedure by the user authentication apparatus
structured as above will be described hereinbleow. FIG. 8 is a
flowchart showing a fingerprint enrollment procedure by the
fingerprint enrollment apparatus 100. A fingerprint image is
inputted from a user to the input unit 10 of the fingerprint
enrollment apparatus 100 (S10). The classification unit 40
determines the fingerprint width based on the inputted fingerprint
image (S12). If the classification unit 40 judges it to be normal
fingerprint width (A of S12), the feature extraction unit 42
performs a feature extraction processing for the normal fingerprint
width on the fingerprint image (S14). And the identification data
preparation unit 18 prepares the fingerprint identification data
based on the extracted fingerprint feature data (S16), and the
identification data enrollment unit 20 enrolls the fingerprint
identification data 32 in the normal fingerprint width
identification database 34 (S18). The enrollment result display
unit 22 notifies the user of a group "A" of normal fingerprint
width (S20).
[0064] If the classification unit 40 determines it to be narrow
fingerprint width (B of S12), the feature extraction unit 42
performs a feature extraction processing for narrow fingerprint on
the fingerprint image (S24). And the identification data
preparation unit 18 prepares the fingerprint identification data
based on the extracted fingerprint feature data (S26), and the
identification data enrollment unit 20 enrolls the fingerprint
identification data 32 in the narrow fingerprint width
identification database 36 (S28). The enrollment result display
unit 22 notifies the user of a group "B" of normal fingerprint
width (S30).
[0065] FIG. 9 is a flowchart showing a fingerprint authentication
procedure by the fingerprint authentication apparatus 200. A
fingerprint image is inputted from a user to the input unit 10 of
the fingerprint authentication apparatus 200 (S40). The
classification unit 40 determines the fingerprint width based on
the inputted fingerprint image (S42). Described here is a procedure
taken if the classification unit 40 judges it to be normal
fingerprint width (A of S42). The feature extraction unit 42
performs a feature extraction processing for the normal fingerprint
width on the fingerprint image (S44). And the verification data
preparation unit 28 prepares the fingerprint verification data
based on the extracted fingerprint feature data (S46). The
fingerprint identification 24 searches the normal fingerprint width
identification database 34 (S48), and compares the fingerprint
verification data with fingerprint identification data 32 which
have already been enrolled (S50). As a result of comparison, if
fingerprint identification data 32 fit into the fingerprint
verification data exist in the normal fingerprint width
identification database 34 (Y of S50), the identification result
display unit 26 notifies the user of the success of authentication
(S62). And if fingerprint identification data 32 fit into the
fingerprint verification-data do not exist in the normal
fingerprint width identification database 34 (N of S50), the
identification result display unit 26 notifies the user of the
failure of authentication (S64)
[0066] Described next is a procedure taken if the classification
unit 40 judges the fingerprint width to be normal fingerprint width
(B of S42). The feature extraction unit 42 performs a feature
extraction processing for the narrow fingerprint width on the
fingerprint image (S54). And the verification data preparation unit
28 prepares the fingerprint verification data based on the
extracted fingerprint feature data (S56). The fingerprint
identification 24 searches the narrow fingerprint width
identification database 36 (S58), and compares the fingerprint
verification data with fingerprint identification data 32 which
have already been enrolled (S60). As a result of comparison, if
fingerprint identification data 32 fit into the fingerprint
verification data exist in the narrow fingerprint width
identification database 36 (Y of S60), the identification result
display unit 26 notifies the user of the success of authentication
(S62). And if fingerprint identification data 32 fit into the
fingerprint verification data do not exist in the narrow
fingerprint width identification database 36 (N of S60), the
identification result display unit 26 notifies the user of the
failure of authentication (S64).
[0067] According to the first embodiment, the inputted fingerprint
image is automatically classified in such a manner as to belong to
the applicable one of a plurality of groups and at the same time
the fingerprint feature data are extracted using the feature
extraction methods suitable for the respective groups. Thus, the
convenience of a user is improved and at the same time the
fingerprint feature data can be extracted with high accuracy.
Furthermore, the feature extraction method to extract the
fingerprint feature data is changed according to the degree of
density in fingerprints, so that an extraction method suitable for
the condition of a fingerprint can be carried out. Furthermore, the
number of ridge lines and the interval thereof is determined
according to the density of fingerprints, so that the fingerprints
can be determined accurately. Furthermore, the classified group can
be reliably presented to the user.
[0068] The fingerprint identification data are enrolled by
classifying them into a plurality of groups. At the same time a
group to which the fingerprint verification data are to belong is
automatically decided and the authentication is conducted based on
the verification fingerprint data that actually belongs to the
applicable group. As a result, the convenience of a user is
improved and at the same time the search efficiency and
authentication accuracy are improved. The resolution for image
processing as well as the filter through which to extract feature
points are switched to those suitable for the fingerprint width.
This absorbs the differences in the physical characteristics and
thus can identify the much larger number of users. The search
efficiency and the authentication accuracy can be improved by
separating physically or logically the fingerprint identification
data per classification.
[0069] A structure according to the first embodiment is such that
the fingerprint enrollment apparatus 100 and the fingerprint
authentication apparatus 200 are separately provided. The structure
may be of such an integrally combined type that the fingerprint
enrollment apparatus 100 is contained in the fingerprint
authentication apparatus 200. In such a case, the input unit 10,
the switching control unit 12, the switches 14a and 14b, the
feature extraction unit 42 and the like can be put to the common
use, so that the structure of an personal authentication apparatus
can be simplified.
[0070] In the first embodiment, the classification unit 40
specifies as a plurality of groups the two groups which are the
normal fingerprint width group 320a and the narrow fingerprint
width group 320b. However, how to specify the groups is not limited
thereto, and three or more groups may be defined, for instance. For
example, three or more groups may be specified in a manner such
that fingerprint data are classified into a plurality of stages in
accordance with the degree of density in fingerprints. According to
this modification, the fingerprint images can be classified in
further detail.
[0071] In the first embodiment, the identification data enrollment
unit 20 enrolls the fingerprint identification data 32 in the
biological information storage unit 30 for each of a plurality of
fingerprint groups. At this point, the fingerprint identification
data 32 contain the fingerprint feature data extracted by the
feature extraction unit 42. However, what the identification data
enrollment unit 20 operates to do is not limited thereto, and the
identification data enrollment unit 20 may enroll the fingerprint
identification data 32 containing the fingerprint images as they
are, instead of the fingerprint identification data 32 containing
the fingerprint feature data. In this case, too, the classification
may be conducted according to the degree of density in
fingerprints. That is, a storage area in the biological information
storage unit 30 may be divided into regions per classification so
as to enroll a user's fingerprint image. And the identification
data enrollment unit 20 may enroll the fingerprint image inputted
to a corresponding divided storage region in the biological
information storage unit 30, based on the classification determined
by the classification unit 40. According to this modification, the
classification processing performed at the registration of
fingerprint images is automated, so that the convenience for a user
can be improved. That is, it is preferable that data be classified
into any of a plurality of groups.
SECOND EMBODIMENT
[0072] In a personal authentication apparatus based on biological
information, when the biological information on a person to be
authenticated (hereinafter, "person to be authenticated" will be
referred to as "person to be verified" or "authenticatee" also) is
compared with that on a person to be enrolled (hereinafter, "person
to be enrolled" will be referred to simply as "registrant") and
then they coincide to the degree that the physiological
characteristics thereof can be authenticated as the person in
question, the person to be authenticated is authenticated. In the
enrollment apparatus according to the first embodiment, the
respective pieces of information on a plurality of registrants are
classified beforehand into a plurality of groups and are then
enrolled in the applicable one of the groups so as to speed up the
authentication processing. For instance, if such information is a
fingerprint, it can be classified into a plurality of groups in
terms of the width, pattern, termination point or bifurcation point
of ridge line, and the like. If, at the time of authentication, a
decision is made on which group the biological information on a
person to be authenticated belongs to and, thereafter, the only
biological information recorded on the registrant associated with
the thus determined group is to be checked, the authentication
processing can be performed much faster than performing the
comparison processing on all the registrants.
[0073] As the biological information is classified into groups more
finely, the number of data to be compared with the user's
biological information can be reduced. Nevertheless, there is a
possibility that a fingerprint might be classified into a group
different from a proper group depending on conditions when the
biological information is collected from a person to be
authenticated. For example, the pressure of a finger against a
sensor in acquiring a fingerprint is not necessarily constant. Thus
there is a possibility that the group might be decided all
differently depending on a condition when the fingerprints are
taken. Also, the biological information itself changes over the
years. Thus, at the time of authentication it may possibly be
classified into a group different from that determined at the time
of fingerprint enrollment. In such a case, the authentication of a
person to be identified will fail, which should have been
successful in the first place.
[0074] Taking the above factors into consideration, a second
embodiment provides a personal authentication technique by
optimally enrolling the biological information.
[0075] FIG. 10 is a functional block diagram for a personal
authentication apparatus according to a second embodiment. In this
second embodiment, a description will be given where fingerprint
information serves as an example of biological information to be
processed.
[0076] In terms of hardware, each block shown here can be realized
by elements of a computer,. such as a CPU, and a mechanical device.
In terms of software, it can be realized by computer programs or
the like, but drawn and described herein are function blocks that
are realized in cooperation with those. Thus, it is understood by
those skilled in the art that these function blocks can be realized
in a variety of forms such as by hardware only, software only or
the combination thereof.
[0077] A personal authentication apparatus 500 includes a user
interface processing unit 102, an evaluation unit 104, an
authentication unit 106, an enrollment unit 108 and a biological
information storage unit 110.
[0078] The user interface processing unit 102 takes charge of
performing an interface processing. The evaluation unit 104
classifies the fingerprint information acquired via the user
interface processing unit 102, according to the feature thereof.
The "fingerprint information" mentioned above may be a fingerprint
image itself or processed information in which physiological
characteristics are extracted from the fingerprint image to
identify an individual. The biological information storage unit 110
stores the fingerprint information of a registrant. The enrollment
unit 108 records the fingerprint information acquired from the user
interface processing unit 102 in the biological information storage
unit 106, according to a classification conducted by the evaluation
unit 104. The authentication unit 106 checks the fingerprint
information acquired from a person to be authenticated against that
of a registrant stored in the biological information storage unit
110 so as to perform an authentication processing. The
authentication unit 106 decides the success or failure of
authentication based on whether or not in these pieces of
fingerprint information the physiological features to identify an
individual coincide with the information on an authenticatee to the
degree that they can be safely authenticated as a registered
person.
[0079] The user interface processing unit 102 includes a biological
information acquiring unit 112 and an operating unit 114. The
biological information acquiring unit 112 acquires, as biological
information, a fingerprint image from a user. The biological
information acquiring unit 112 further includes a feature
extraction unit 116. The feature extraction unit 116 extracts, from
the fingerprint image, physiological features which are effective
for authenticating an individual. The physiological features in the
fingerprint image include the ridge shape of a fingerprint, feature
points such as the termination point or bifurcation point of a
ridge line, directional vectors of ridge line at a predetermined
point on a ridge line and the width of ridge or the interval
thereof, for example. The operating unit 114 receives operations
from the user. The "operation" mentioned here includes an
instruction as to the start or termination of acquiring the
fingerprint information, for example. Besides the already mentioned
functions, the user interface processing unit 102 may be equipped
with notification functions by which various kinds of information
is displayed to the user or the audio is outputted. For instance,
the acquisition of biological information or the completion of
authentication may be notified to the user via the LED, screen
display, audio or the like.
[0080] The evaluation unit 104 includes an index value calculating
unit 118, a group specifying unit 120 and a boundary condition
determining unit 122.
[0081] The index value calculating unit 118 puts into indices the
physiological features of a fingerprint extracted by the feature
extraction unit 116. The values put into indices will be simply
called "index values" hereinafter. For example, a fingerprint image
is binarized into a black area and a white area, based on a
predetermined threshold value, so that the indexing may be done
using the area ratio thereof. Alternatively, the number of
termination points or bifurcation points of a fingerprint may serve
as the index value. According the second embodiment, two kinds of
indices, namely, a first index value and a second index value are
calculated for a single piece of index information, from such
various aspects as mentioned above. As a modification, many more
kinds of index values may also be calculated.
[0082] An index value is classified into a plurality of groups. For
instance, if the first index value takes on the values ranging from
0 to 100, the groups are set beforehand corresponding respectively
to predetermined ranges in such a manner, for example, that the
groups are classified by "greater than or equal to 0 and less than
10", "greater than or equal to 10 and less than 20" and so forth.
In the similar manner, the groups are set for the second index
value. In what is to follow, if it is intended that a distinction
be made between the group of first index values and that of the
second index values, they will be particularly called "group of
first kind" and "group of second kind".
[0083] The group specifying unit 120 detects to which group the
index value calculated by the index value calculating unit 118
belongs. The biological information storage unit 110 has a
plurality of storage regions that correspond to these groups,
respectively. The biological information storage unit 110 has a
plurality of storage regions (hereinafter referred to as "storage
regions of first kind") which correspond respectively to a
plurality of groups of first kind, and a plurality of storage
regions (hereinafter referred to as "storage regions of second
kind") which correspond respectively to a plurality of groups of
second kind. The biological information storage unit 110 may
realize these storage regions by employing a structure of array
type or list type. For instance, if ten groups are each set as the
groups of first kind and the groups of second kind, then ten
regions are each set as the storage regions of first kind and the
storage regions of second kind.
[0084] The boundary condition determining unit 122 determines
whether a boundary condition holds or not, based on whether the
index value calculated by the index value calculating unit 118 is
close to the boundary of the group specified by the group
specifying unit 120 or not. The boundary condition determining unit
122 determines respectively whether the respective boundary
conditions for the groups of first kind and the groups of second
kind hold or not. For instance, if the first index value is "15",
the group of first kind which indicates the range of "greater than
or equal to 10 and less than 20" is specified. Then, since this
first index value does not lie within "3" from "10" or "20",
namely, "greater than or equal to 10 and less than 13" or "greater
than or equal to 17 or less than 20", the boundary condition does
not hold. If, on the other hand, the index value of first kind is
"18", the boundary condition holds this time. When the boundary
condition holds, the group specifying unit 120 specifies two groups
which lie across the boundary. In the example mentioned just above,
if the first index value is "18", the range of "greater than or
equal to 20 or less than 30" will also be one to be specified as
the group of first kind, in addition to the range of "greater than
or less than 10 and less than 20".
[0085] The enrollment unit 108 enrolls the fingerprint image in a
storage region, of the biological information storage unit 110,
corresponding to the group specified by the group specifying unit
120. That is, the enrollment unit 108 enrolls the fingerprint
information in storage regions of first kind and storage regions of
second kind, respectively. For instance, if the boundary condition
holds for the first index value and it does not hold for the second
index value, the enrollment unit 108 records the fingerprint
information in the total of three storage regions consisting of two
storage regions of first kind and one storage region of second
kind.
[0086] FIG. 11 illustrates a data structure in a biological
information storage unit 110.
[0087] In the biological information storage unit 110, the storage
area is divided and classified into a plurality of storage regions
that correspond to a plurality of groups. A range ID column 150
shows IDs by which to identify each group (hereinafter referred to
as "range ID"). A group column 152 shows the range of index values
belonging to a group. For instance, the range ID "0" corresponds to
a group in which the index values lie in the range of "greater than
or equal to 0 and less than 10" (this is expressed as
"0.ltoreq.AND<20" in FIG. 11). The range ID "1" corresponds to a
group in which the index values lie in the range of "greater than
or equal to 10 and less than 20".
[0088] A first index value column 154 indicates a registrant
relevant to the first index value, and a second index value column
156 indicates a registrant relevant to the second index value. In
the first index value column 154 and the second index value column
156, IDs by which to specify a registrant (hereinafter referred to
as "registrant ID") are recorded. For instance, the first index
value about the fingerprint information on a registrant of the
registrant ID "01" corresponds to the range ID "1", namely,
"greater than or equal to 10 and less than 20". In other words, the
range ID of the group of first kind under which this registrant
falls is "1". On the other hand, the second index value about the
fingerprint information of the same registrant of the registrant ID
"01" corresponds to "greater than or equal to 60 and less than 70"
of the range ID "6". In other words, the range ID of the group of
second kind corresponds to "6". The first index value about the
fingerprint information on a registrant of the registrant ID "02"
is recorded in both the range ID "0" and the range ID "1" in the
group of first kind. A plurality of groups of first kind are
specified as values to be checked because the boundary condition
for the first index value of this registrant holds true there.
[0089] The group specifying unit 120 determines to which group the
index value calculated by the index value calculating unit 118
belongs to, by referring to the group column 152. If the boundary
condition is determined to hold true by the boundary condition
determining unit 122, the group specifying unit 120 specifies two
groups that surround or lie across the boundary, by the group
column 152. The fingerprint information is enrolled in a region
corresponding to the thus specified group.
[0090] FIG. 12 is a flowchart showing a processing procedure when a
fingerprint is enrolled in a personal authentication apparatus.
[0091] First, a user presses a surface of his/her thumb against a
fingerprint sensor. The biological information acquiring unit 112
acquires, as user's fingerprint information, a fingerprint image
via this fingerprint sensor (S110). The fingerprint sensor may be a
well-known sensor such as an optical sensor or a pressure-sensitive
sensor. The personal authentication apparatus 500 may include
therein a fingerprint sensor itself or may receive the fingerprint
image acquired by an external fingerprint sensor via a
communication line. The feature extraction unit 116 extracts from
the acquired fingerprint image a physiological feature by which to
identify an individual (S112). The index value calculating unit 118
calculates the first index value and the second index value based
on the extracted physiological feature (S114). By referring to the
group column 152, the group specifying unit 120 specifies the group
of first kind and the group of second kind for the respective index
values (S116).
[0092] Next, the boundary condition determining unit 122 determines
whether a boundary condition holds for each of the groups specified
(S118). If the boundary condition holds (Y of S118), the group
specifying unit 120 specifies two groups that surround the boundary
(S120). If the boundary condition does not hold (N of S118), the
processing of S120 will be skipped. For instance, if the boundary
condition for the groups of first kind holds, then two groups of
first kind are specified and if the boundary condition of the group
of second kind does not hold, then a single group of second kind
will be specified. As a result, three groups will have been
specified in this case.
[0093] As another concrete example, suppose that the boundary
condition holds if the index value is within "3" from the boundary
value of a group. Here, suppose also that the first index value and
the second index value calculated by the index value calculating
unit 118 based on the biological information of a fingerprint is
"11" and "54", respectively. Then, the group specifying unit 120
specifies the group-of-first-kind range ID and the
group-of-second-kind range ID as "1" and "5", respectively. Since
the first index value lies within 3 from the boundary value "10" of
the group of first kind "greater than or equal to 10 and less than
20", the boundary condition determining unit 122 determines that
the boundary condition holds true. The group specifying unit 120
specifies also the range ID "0", in addition to the range ID "1",
as a group of first kind corresponding to the first index value
"11". On the other hand, the boundary condition does not hold true
for the group of second kind. Hence, the group of second kind
belongs to the range ID "5" only. As a result, the total of three
groups is identified.
[0094] The enrollment unit 108 specifies storage regions
corresponding to a plurality of groups specified in Step S116 or
S120 (S122). The enrollment unit 108 records the acquired
fingerprint information in each of the specified storage regions
(S124). In this manner, the fingerprint information is enrolled in
a plurality of storage regions of the biological information
storage unit 110. As for the example mentioned above, the result is
that the same fingerprint information is recorded in the three
different storage regions.
[0095] FIG. 13 is a flowchart showing the first example of a
processing procedure in the authentication of fingerprints.
[0096] The biological information acquiring unit 112 acquires, as
fingerprint information, a fingerprint image of a person to be
identified (S130). The feature extraction unit 116 extracts from
this acquired fingerprint image a physiological feature to identify
an individual (S132). The index calculating unit 118 calculates the
first index value and the second index value based on this
extracted physiological feature (S134). The group specifying unit
120 specifies applicable first and second groups (S136). The
boundary condition determining unit 122 decides whether a boundary
condition holds for each index value or not (S138). If the boundary
condition holds (Y of S138), the group specifying unit 120
specifies two groups that lie across the boundary (S140). If the
boundary condition does not hold (N of S138), the processing of
S140 is skipped. In this manner, one on more groups are specified
for each of the first index value and the second index value.
[0097] The authentication unit 106 specifies a storage region of
first kind and a storage region of second kind corresponding to the
group of first kind and the group of second kind specified in S136
or S140. The authentication unit 106 checks the fingerprint
information enrolled in a plurality of these storage regions
against the fingerprint information acquired in Step S130, and then
checks if they coincide to the degree that the physiological
feature matches to identify a registrant (S142). When a registrant
corresponding to an authenticatee can be identified for the
fingerprint information recorded in either a storage region of
first kind or a storage region of second kind, the authentication
unit may determine the authentication to be successful.
Alternatively, authentication may be determined successful on the
condition that a registrant corresponding to an authenticatee can
be identified for the fingerprint information recorded respectively
in both a storage region of first kind and a storage region of
second kind. When the authentication is successful (Y of S144), the
user interface processing unit 102 indicates to the authenticatee
that the authentication has been successful (S146). When
unsuccessful (N of S144), the user interface processing unit 102
indicates to the authenticate that the authentication has
failed.
[0098] According to such a mode of carrying out the present
invention as the second embodiment described above, the fingerprint
information is recorded in a plurality of storage regions based on
a plurality of index values. As for index information which is
rather hard to be classified in terms of a predetermined index
value, a plurality of groups are specified as described in Step
S120, and a plurality of storage regions are to be enrolled as
described in Step S122. Thus, the authentication accuracy can be
kept high while the advantage of the classification scheme is made
full use of. For instance, if the first index value defies
classification as to the fingerprint information on an
autheticatee, a boundary condition holds and therefore a plurality
of storage regions are to be checked. To this end, even if an
intended group is likely to change from one to another due to an
acquisition condition of a fingerprint or circumstances such as
weather at the time of authentication, an identification processing
can be carried out optimally.
[0099] FIG. 14 is a flowchart showing the second example of a
processing procedure in the authentication of fingerprints.
[0100] The processing steps from S150 through S156 are similar to
those from S130 through 136, respectively, described with reference
to FIG. 13. When a group is specified in Step S156, the
authentication unit 106 checks the fingerprint information on an
authenticatee against the fingerprint information on a registrant
recorded in the group (S158). Here, it is supposed that
authentication is determined successful only if the registrant
corresponding to an authenticatee can be specified for the
fingerprint information recorded in both the storage region of
first kind and the storage region of second kind.
[0101] If authentication is successful (Y of S160), the user
interface processing unit 102 indicates that the authentication has
been successful (S168). If the authentication is unsuccessful (N of
S160), the group specifying unit 120 changes the group on which a
comparison processing is to be performed (S162). The authentication
unit 106 extends the coverage of a comparison processing to be
performed to a storage region corresponding to a newly specified
group, and carries out another comparison processing (S163).
[0102] For instance, if a registrant corresponding to an
authenticatee cannot be identified for fingerprint information
recorded in a storage region of first kind, the group specifying
unit 120 extends the coverage of a comparison processing so that
the other storage regions of first kind are also subjected to this
comparison processing. In Step S162, the group specifying unit 120
may change the comparison coverage so that all of the groups of
first kind are subjected to the comparison processing. Or, the
group specifying unit 120 may change the comparison coverage so
that a group of first kind adjacent to the group of first kind
specified in Step S156 is also subjected to a comparison
processing. Here, a change is made in a manner such that two groups
of first kind adjacent to the group of first kind specified in Step
S156 are now subjected to the comparison processing.
[0103] As an example of the above, suppose that a registrant
corresponding to an authenticatee can be identified in a storage
region of second kind corresponding to a group of second kind
specified in Step S156. On the other hand, suppose that the
registrant corresponding to the authenticatee cannot be identified
in a storage region of first kind corresponding to a group of first
kind specified in Step S156. In this case, in Step S162 the group
specifying unit 120 newly specifies two groups of first kind
adjacent to the group of first kind specified in Step S156. Then in
Step S163, the fingerprint information enrolled in the storage
regions of first kind corresponding to these groups of first kind
is compared with the fingerprint information on an
authenticatee.
[0104] If the identification of the registrant corresponding to the
authenticatee is successful in the newly specified storage regions
on which the comparison processing is to be performed and therefore
the authentication is successful (Y of S164), the enrollment unit
108 deletes the fingerprint information recorded in the storage
regions with which the authentication has been successful and
re-registers the fingerprint information acquired in Step S150 in
the storage region corresponding to the group specified in Step
S156 (S166). Then the user interface processing unit 102 indicates
that the biological authentication has been successful (S166). If,
on the other hand, the authentication is unsuccessful in Step S164
(N of S164), the user interface processing unit 102 indicates that
the authentication has been unsuccessful (S170).
[0105] If a registrant is authenticated successfully in Step S164,
the group corresponding to the fingerprint information on an
authenticatee will differ from the applicable group at the time of
enrollment. In such a case, the fingerprint information acquired at
the time of enrollment is re-registered in a storage region
corresponding to a group determined when the acquired fingerprint
information is authenticated.
[0106] The biological information is information which is effective
in identifying an individual. However, it may change as a person
grows older. For instance, as a child grows over the years, the
size of a finger changes and, along with this change, the interval
of ridge lines changes also. For this reason, there is a
probability that the first index value and/or the second index
value changes in comparison with those obtained at the time of
enrollment and therefore the applicable group itself changes to a
different group. According to the second embodiment, even when the
authentication is not successful in Step S160, another
identification processing is still possible by comparing the
acquired information with biological information on a registrant
stored in a different storage region or different storage regions.
Furthermore, the most recent fingerprint information acquired at
authentication is re-registered and updated in a storage region
corresponding to a new group specified in Step S156. Thus, every
time the identification processing is carried out, the applicable
group can be corrected. As a result, the structure and method
employed in the second embodiment can automatically cope with the
deterioration with age, so that the high authentication accuracy
can be retained for the long period of time. From the first time
enrollment on, the biological information is subjected to a
re-registration processing as necessary at every occasion of
verification, so that there can be provided a user authentication
apparatus 500 which is highly utilizable to the user.
[0107] The present invention has been described based on some
embodiments which are only exemplary. It is understood by those
skilled in the art that there exist other various modifications to
the combination of each component and process described above and
that such modifications are within the scope of the present
invention.
[0108] As such modifications, the user authentication apparatus has
been described above using the fingerprint identification as an
example. However, the present invention is also applicable to any
type of authentication using such biological information as palm
print, face image, iris image, retina image, venous information or
voiceprint. For example, in the case of identifying palm print,
data may be loosely classified by adult/child, gender, wideness of
a finger and so forth, so that the resolution or the like can be
optimized in accordance with the resulting classification. In the
case of identifying iris, data may be roughly sorted out
respectively by different colors of eyes, so that the image
processing method in actual use can be switched. In the case of
voiceprint, data may be classified by pitch of voice, gender,
adult/child, age group and so forth, so that the parameters for
voice recognition and the like can be adjusted per
classification.
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